Update README.md

README.md

@@ -1,10 +1,14 @@
----
-license: cc-by-sa-4.0
-task_categories:
-- audio-classification
-size_categories:
-- 1M<n<10M
----
+---
+license: cc-by-sa-4.0
+task_categories:
+- audio-classification
+size_categories:
+- 1M<n<10M
+configs:
+- config_name: default
+  data_files: "*.tar"
+  default: true
+---
 
 # VoxCeleb2 - dev set
 
@@ -17,16 +21,22 @@ There are 1,092,009 samples covering 5,994 unique speakers. The dataset is split
 ```python
 import torchaudio
 import webdataset as wds
+from datasets import load_dataset
 
 def decode_audio(sample):
     audio, fs = torchaudio.load(sample.pop("m4a"))  # requires FFMPEG to decode AAC. refer to torchaudio doc
-    # optional resample
+    # optionally resample audio and other pre-processing
     sample["audio"] = audio
     return sample
 
+# using webdataset library
 ds = wds.WebDataset("https://huggingface.co/datasets/gaunernst/voxceleb2-dev-wds/resolve/main/voxceleb2-dev-{0000..0778}.tar")
 ds = ds.map(decode_audio)
+next(iter(ds))
 
+# using HF datasets library
+ds = load_dataset("gaunernst/voxceleb2-dev-wds", streaming=True)
+ds = ds.map(decode_audio)
 next(iter(ds))
 ```